AI RESEARCH

Counterfactual Intervention Feature Transfer for Visible-Infrared Person Re-identification

arXiv CS.CV

ArXi:2208.00967v4 Announce Type: replace Graph-based models have achieved great success in person re-identification tasks recently, which compute the graph topology structure (affinities) among different people first and then pass the information across them to achieve stronger features. But we find existing graph-based methods in the visible-infrared person re-identification task (VI-ReID) suffer from bad generalization because of two issues: 1) train-test modality balance gap, which is a property of VI-ReID task. The number of two modalities data are balanced in the.